Untraceable electronic mail, return addresses, and digital pseudonyms
Communications of the ACM
Perfect Matching Disclosure Attacks
PETS '08 Proceedings of the 8th international symposium on Privacy Enhancing Technologies
Two-sided statistical disclosure attack
PET'07 Proceedings of the 7th international conference on Privacy enhancing technologies
Practical traffic analysis: extending and resisting statistical disclosure
PET'04 Proceedings of the 4th international conference on Privacy Enhancing Technologies
Countering statistical disclosure with receiver-bound cover traffic
ESORICS'07 Proceedings of the 12th European conference on Research in Computer Security
Understanding statistical disclosure: a least squares approach
PETS'12 Proceedings of the 12th international conference on Privacy Enhancing Technologies
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Statistical disclosure is a well-studied technique that an attacker can use to uncover relations between users in mix-based anonymity systems. Prior work has focused on finding the receivers to whom a given targeted user sends. In this paper, we investigate the effectiveness of statistical disclosure in finding all of a users' contacts, including those from whom she receives messages. To this end, we propose a new attack called the Reverse Statistical Disclosure Attack (RSDA). RSDA uses observations of all users sending patterns to estimate both the targeted user's sending pattern and her receiving pattern. The estimated patterns are combined to find a set of the targeted user's most likely contacts. We study the performance of RSDA in simulation using different mix network configurations and also study the effectiveness of cover traffic as a countermeasure. Our results show that that RSDA outperforms the traditional SDA in finding the user's contacts, particularly as the amounts of user traffic and cover traffic rise.